Resource-aware Orchestration of IoT Applications in Edge-Cloud Continuum with 6G

Edge computing and Internet of Things (IoT) avail a technological environment where everybody (human, objects) can join the internet to process, store, collect and exchange data from the surrounding environment. Embedding of large scale IoT applications to the network of distributed computational resources has become a challenging part of the edge-cloud continuum paradigm. Due to the high distance between the local devices and the cloud, there would be an issue for latency sensitive and energy-intensive applications like healthcare (i.e., patient remote monitoring, wearable health devices), and AR/VR. The edge computing paradigm resolves these challenges by providing data resources and services closer to data sources and end devices at the network's edge. This research will focus on investigating challenges and issues for the combined multi-tier orchestration in edge-cloud continuum consisting of local edge nodes, edge servers and cloud servers with emphasis on future 6G systems. The PhD research will focus on resource and QoS-aware IoT application deployment and resource orchestration in local edge-cloud continuum three-tier architecture in 6G.